1. Field of the Invention
The present invention generally relates to maximum-likelihood decoding, and in particular to a method of generating the reliability of data decoded by Viterbi decoding and a maximum-likelihood decoder using the method.
2. Description of the Related Art
In general, the maximum-likelihood decision circuit (MLD) of a Viterbi decoder generates decoded data as hard-decision information which is either 0 or 1. Although there has been soft-decision decoding, such a soft-decision scheme is only designed to receive an input analog signal as quantized multi-level signal so as to increase its coding gain.
In order to achieve the more increased reliability of decoded data, a soft-decision decoded information generator has been proposed in Japanese Patent Unexamined Publication NO. 3-154521, which is shown in FIG. 1.
Referring to FIG. 1, when receiving an input encoded (or received) sequence, an ACS (add-compare-select) unit 1 generates a survivor path metric and a survivor path selection signal for each state or node of the trellis diagram at each time. More specifically, a branch metric generator, receiving the input sequence, calculates two branch metrics for each state corresponding to the respective two paths leading to that state. In each of ACS circuits ACS.sub.1 -ACS.sub.n (n is the number of states of the trellis), these two branch metrics are added to the path metrics of the preceding two states, respectively, to produce two path metrics for that state. Subsequently, by comparing these path metrics, the one which has a larger path metric is selected as a survivor path at the state. The path selection information for the survivor paths are stored into a path memory 2 and the respective path metrics for the survivor paths are output to the MLD 3 and a path metric comparator 4.
The path metric comparator 4 compares the path metrics to each other to detect the maximum path metric from them. After the respective differences between the maximum path metric and other path metrics are calculated, the differences are accumulated to produce a value K as likelihood information, which is output to a soft-decision decoded data generator 5. In cases where four path metrics M.sub.1 -M.sub.4 are generated by the ACS.sub.1 -ACS.sub.4, the path metric comparator 4 performs the following calculations:
M=max(M.sub.1, M.sub.2, M.sub.3, M.sub.4) and PA1 K=.SIGMA.(M-Mi).
Since the value K becomes larger as the output sequence is more likely, the value K serves as likelihood information.
Receiving the likelihood information K from the path metric comparator 4 and the most likely decoded data sequence from the MLD 3, a soft-decision decoded data generator 5 produces a soft-decision decoded data sequence such that the most likely decision decoded data bit is added as MSB (Most Significant Bit) to the data bits of the likelihood information K.
According to the conventional decoder, however, the likelihood information K is generated by the path metric comparator 4 directly using the path metrics Mi as described above. Such a method of generating the likelihood information, in some cases, has a disadvantage that the magnitude of the likelihood information K is varied depending on variations of the input signal condition. Especially, in the case of a Viterbi decoder for use in MLSE (maximum-likelihood sequence estimation) configuration, the path metric is varied with the magnitude of input data value and/or the amount of inter-symbol interference, which leads to changed criterion of the reliability of decoded data according to input conditions. Therefore, a likelihood information generator such as the path metric comparator 4 cannot generate the stable and accurate likelihood information. In other words, soft-decision decoded data cannot be obtained with sufficient reliability.